Evolution of competing strategies in a threshold model for task allocation

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.
Original languageEnglish
Title of host publicationSoftware engineering, artificial intelligence, networking and parallel/distributed computing 2010
Subtitle of host publicationSNPD2010
EditorsRoger Lee
Place of PublicationBerlin Heidelberg
PublisherSpringer
Pages85-98
Number of pages14
ISBN (Electronic)978-3-642-13265-0
ISBN (Print)978-3-642-13264-3
DOIs
Publication statusPublished - 2010

Publication series

NameStudies in computational Intelligence
PublisherSpringer
Volume295
ISSN (Print)1860-949X

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Evolutionary algorithms
Communication

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Goldingay, H., & van Mourik, J. (2010). Evolution of competing strategies in a threshold model for task allocation. In R. Lee (Ed.), Software engineering, artificial intelligence, networking and parallel/distributed computing 2010: SNPD2010 (pp. 85-98). (Studies in computational Intelligence; Vol. 295). Berlin Heidelberg: Springer. https://doi.org/10.1007/978-3-642-13265-0_7
Goldingay, Harry ; van Mourik, Jort. / Evolution of competing strategies in a threshold model for task allocation. Software engineering, artificial intelligence, networking and parallel/distributed computing 2010: SNPD2010. editor / Roger Lee. Berlin Heidelberg : Springer, 2010. pp. 85-98 (Studies in computational Intelligence).
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abstract = "A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.",
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Goldingay, H & van Mourik, J 2010, Evolution of competing strategies in a threshold model for task allocation. in R Lee (ed.), Software engineering, artificial intelligence, networking and parallel/distributed computing 2010: SNPD2010. Studies in computational Intelligence, vol. 295, Springer, Berlin Heidelberg, pp. 85-98. https://doi.org/10.1007/978-3-642-13265-0_7

Evolution of competing strategies in a threshold model for task allocation. / Goldingay, Harry; van Mourik, Jort.

Software engineering, artificial intelligence, networking and parallel/distributed computing 2010: SNPD2010. ed. / Roger Lee. Berlin Heidelberg : Springer, 2010. p. 85-98 (Studies in computational Intelligence; Vol. 295).

Research output: Chapter in Book/Report/Conference proceedingChapter

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Goldingay H, van Mourik J. Evolution of competing strategies in a threshold model for task allocation. In Lee R, editor, Software engineering, artificial intelligence, networking and parallel/distributed computing 2010: SNPD2010. Berlin Heidelberg: Springer. 2010. p. 85-98. (Studies in computational Intelligence). https://doi.org/10.1007/978-3-642-13265-0_7